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Field
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coding . Have a degree in Computer Science/Computer Engineering. Possessing a Master’s or PhD degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge
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environmental factors associated with CKD incidence and trends. Apply advanced statistical and machine learning methods, including semi-supervised cluster analysis, to characterize populations with diabetes and
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including historical linguistics, semantics, pragmatics, computational linguistics, phonology, or sociolinguistics. We would like to see candidates who can communicate with and learn from both linguists and
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Nair, to study how machine learning models and neural circuits in the brain process states of emotion. The Nair group combines cutting-edge systems neuroscience tools with the development of new AI
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 7 hours ago
tokenization, text classification, and named entity recognition. Compare traditional rule-based NLP approaches with modern machine learning-based approaches and articulate when each may be appropriate in a
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP
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with vessel protected volume estimates to identify safety-buffer overlaps, developing multi-agent path-planning, and machine-learning methods for corridor allocation, airspace capacity optimisation, and
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, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow
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and research in several areas. These include, but are not limited to: Adversarial location and network interdiction models Adversarial machine learning attacks and defense (e.g., against Bayesian
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, procurement, or grant administration will be an added advantage. Experience in areas such as Machine Learning, Deep Learning, Computer Vision, Large Language Models, Data Analytics, or Intelligent Systems will